Field
The disclosed embodiments relate to in-session recommendations. More specifically, the disclosed embodiments relate to techniques for performing regularized model adaptation for in-session recommendations.
Related Art
Analytics may be used to discover trends, patterns, relationships, and/or other attributes related to large sets of complex, interconnected, and/or multidimensional data. In turn, the discovered information may be used to gain insights and/or guide decisions and/or actions related to the data. For example, business analytics may be used to assess past performance, guide business planning, and/or identify actions that may improve future performance.
However, significant increases in the size of data sets have resulted in difficulties associated with collecting, storing, managing, transferring, sharing, analyzing, and/or visualizing the data in a timely manner. For example, conventional software tools and/or storage mechanisms may be unable to handle petabytes or exabytes of loosely structured data that is generated on a daily and/or continuous basis from multiple, heterogeneous sources. Instead, management and processing of “big data” may require massively parallel software running on a large number of physical servers and/or nodes, as well as synchronization among the servers and/or nodes.
Consequently, big data analytics may be facilitated by mechanisms for efficiently and/or effectively collecting, storing, managing, compressing, transferring, sharing, analyzing, and/or visualizing large data sets.
In the figures, like reference numerals refer to the same figure elements.